Overview

Dataset statistics

Number of variables88
Number of observations1190
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory818.2 KiB
Average record size in memory704.1 B

Variable types

Numeric7
Categorical81

Alerts

SIM_GIPERT has constant value "0.0"Constant
ZSN_A has constant value "0.0"Constant
nr_11 has constant value "0.0"Constant
nr_01 has constant value "0.0"Constant
nr_02 has constant value "0.0"Constant
nr_03 has constant value "0.0"Constant
nr_04 has constant value "0.0"Constant
nr_07 has constant value "0.0"Constant
nr_08 has constant value "0.0"Constant
np_01 has constant value "0.0"Constant
np_04 has constant value "0.0"Constant
np_05 has constant value "0.0"Constant
np_07 has constant value "0.0"Constant
np_08 has constant value "0.0"Constant
np_09 has constant value "0.0"Constant
np_10 has constant value "0.0"Constant
endocr_01 has constant value "0.0"Constant
endocr_02 has constant value "0.0"Constant
endocr_03 has constant value "0.0"Constant
zab_leg_01 has constant value "0.0"Constant
zab_leg_02 has constant value "0.0"Constant
zab_leg_03 has constant value "0.0"Constant
zab_leg_04 has constant value "0.0"Constant
zab_leg_06 has constant value "0.0"Constant
O_L_POST has constant value "0.0"Constant
K_SH_POST has constant value "0.0"Constant
MP_TP_POST has constant value "0.0"Constant
SVT_POST has constant value "0.0"Constant
GT_POST has constant value "0.0"Constant
FIB_G_POST has constant value "0.0"Constant
post_im has constant value "0.0"Constant
IM_PG_P has constant value "0.0"Constant
n_r_ecg_p_01 has constant value "0.0"Constant
n_r_ecg_p_02 has constant value "0.0"Constant
n_r_ecg_p_03 has constant value "0.0"Constant
n_r_ecg_p_04 has constant value "0.0"Constant
n_r_ecg_p_05 has constant value "0.0"Constant
n_r_ecg_p_06 has constant value "0.0"Constant
n_r_ecg_p_08 has constant value "0.0"Constant
n_r_ecg_p_09 has constant value "0.0"Constant
n_r_ecg_p_10 has constant value "0.0"Constant
n_p_ecg_p_01 has constant value "0.0"Constant
n_p_ecg_p_03 has constant value "0.0"Constant
n_p_ecg_p_04 has constant value "0.0"Constant
n_p_ecg_p_05 has constant value "0.0"Constant
n_p_ecg_p_06 has constant value "0.0"Constant
n_p_ecg_p_07 has constant value "0.0"Constant
n_p_ecg_p_08 has constant value "0.0"Constant
n_p_ecg_p_09 has constant value "0.0"Constant
n_p_ecg_p_10 has constant value "0.0"Constant
n_p_ecg_p_11 has constant value "0.0"Constant
n_p_ecg_p_12 has constant value "0.0"Constant
fibr_ter_01 has constant value "0.0"Constant
fibr_ter_02 has constant value "0.0"Constant
fibr_ter_03 has constant value "0.0"Constant
fibr_ter_05 has constant value "0.0"Constant
fibr_ter_06 has constant value "0.0"Constant
fibr_ter_07 has constant value "0.0"Constant
fibr_ter_08 has constant value "0.0"Constant
R_AB_1_n has constant value "0.0"Constant
R_AB_2_n has constant value "0.0"Constant
R_AB_3_n has constant value "0.0"Constant
NITR_S has constant value "0.0"Constant
NA_R_2_n has constant value "0.0"Constant
NA_R_3_n has constant value "0.0"Constant
NOT_NA_2_n has constant value "0.0"Constant
NOT_NA_3_n has constant value "0.0"Constant
B_BLOK_S_n has constant value "0.0"Constant
ASP_S_n has constant value "0.0"Constant
TIKL_S_n has constant value "0.0"Constant
TRENT_S_n has constant value "0.0"Constant
ANT_CA_S_n is highly overall correlated with GEPAR_S_n and 2 other fieldsHigh correlation
FK_STENOK is highly overall correlated with STENOK_ANHigh correlation
GEPAR_S_n is highly overall correlated with ANT_CA_S_nHigh correlation
LID_S_n is highly overall correlated with ANT_CA_S_n and 1 other fieldsHigh correlation
NOT_NA_1_n is highly overall correlated with ANT_CA_S_n and 1 other fieldsHigh correlation
STENOK_AN is highly overall correlated with FK_STENOKHigh correlation
ant_im is highly overall correlated with inf_im and 1 other fieldsHigh correlation
inf_im is highly overall correlated with ant_imHigh correlation
lat_im is highly overall correlated with ant_imHigh correlation
NOT_NA_1_n is highly imbalanced (52.4%)Imbalance
STENOK_AN has 45 (3.8%) zerosZeros
ant_im has 29 (2.4%) zerosZeros
L_BLOOD has 71 (6.0%) zerosZeros
TIME_B_S has 89 (7.5%) zerosZeros

Reproduction

Analysis started2024-05-17 09:10:13.137332
Analysis finished2024-05-17 09:10:27.923160
Duration14.79 seconds
Software versionydata-profiling v4.8.3
Download configurationconfig.json

Variables

AGE
Real number (ℝ)

Distinct60
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-1.865921 × 10-16
Minimum-2.6718422
Maximum2.7062007
Zeros3
Zeros (%)0.3%
Negative561
Negative (%)47.1%
Memory size9.4 KiB
2024-05-17T16:10:28.141802image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum-2.6718422
5-th percentile-1.7306847
Q1-0.65507613
median0.061996254
Q30.68943459
95-th percentile1.5857751
Maximum2.7062007
Range5.3780429
Interquartile range (IQR)1.3445107

Descriptive statistics

Standard deviation1.0004204
Coefficient of variation (CV)-5.3615368 × 1015
Kurtosis-0.25072477
Mean-1.865921 × 10-16
Median Absolute Deviation (MAD)0.71707238
Skewness-0.1380738
Sum-2.2026825 × 10-13
Variance1.000841
MonotonicityNot monotonic
2024-05-17T16:10:28.403646image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.2412643498 61
 
5.1%
0.1516303019 59
 
5.0%
0.4205324458 50
 
4.2%
-0.7447101778 47
 
3.9%
0.3308983978 47
 
3.9%
0.8687026856 43
 
3.6%
0.0619962539 39
 
3.3%
-0.4758080339 38
 
3.2%
-0.296539938 37
 
3.1%
-0.117271842 36
 
3.0%
Other values (50) 733
61.6%
ValueCountFrequency (%)
-2.671842209 4
 
0.3%
-2.537391137 3
 
0.3%
-2.447757089 2
 
0.2%
-2.358123041 4
 
0.3%
-2.268488993 5
 
0.4%
-2.178854945 2
 
0.2%
-2.089220897 13
1.1%
-1.999586849 10
0.8%
-1.909952801 4
 
0.3%
-1.820318753 6
0.5%
ValueCountFrequency (%)
2.706200669 2
 
0.2%
2.482115549 4
 
0.3%
2.392481501 2
 
0.2%
2.302847453 1
 
0.1%
2.213213405 1
 
0.1%
2.123579357 3
 
0.3%
2.033945309 10
0.8%
1.944311261 4
 
0.3%
1.854677213 7
0.6%
1.765043165 11
0.9%

SEX
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size87.7 KiB
0.7088901554720962
792 
-1.4106557867685932
398 

Length

Max length19
Median length18
Mean length18.334454
Min length18

Characters and Unicode

Total characters21818
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.7088901554720962
2nd row0.7088901554720962
3rd row0.7088901554720962
4th row-1.4106557867685932
5th row0.7088901554720962

Common Values

ValueCountFrequency (%)
0.7088901554720962 792
66.6%
-1.4106557867685932 398
33.4%

Length

2024-05-17T16:10:28.618690image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:28.824985image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.7088901554720962 792
66.6%
1.4106557867685932 398
33.4%

Most occurring characters

ValueCountFrequency (%)
0 3566
16.3%
5 2778
12.7%
7 2380
10.9%
8 2380
10.9%
6 1986
9.1%
9 1982
9.1%
2 1982
9.1%
1 1588
7.3%
. 1190
 
5.5%
4 1190
 
5.5%
Other values (2) 796
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20230
92.7%
Other Punctuation 1190
 
5.5%
Dash Punctuation 398
 
1.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3566
17.6%
5 2778
13.7%
7 2380
11.8%
8 2380
11.8%
6 1986
9.8%
9 1982
9.8%
2 1982
9.8%
1 1588
7.8%
4 1190
 
5.9%
3 398
 
2.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 398
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 21818
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3566
16.3%
5 2778
12.7%
7 2380
10.9%
8 2380
10.9%
6 1986
9.1%
9 1982
9.1%
2 1982
9.1%
1 1588
7.3%
. 1190
 
5.5%
4 1190
 
5.5%
Other values (2) 796
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21818
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3566
16.3%
5 2778
12.7%
7 2380
10.9%
8 2380
10.9%
6 1986
9.1%
9 1982
9.1%
2 1982
9.1%
1 1588
7.3%
. 1190
 
5.5%
4 1190
 
5.5%
Other values (2) 796
 
3.6%

INF_ANAM
Categorical

Distinct4
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size88.0 KiB
-0.6491580568765987
778 
0.6770189176867532
267 
2.0031958922501047
94 
2.6662843795317808
 
51

Length

Max length19
Median length19
Mean length18.653782
Min length18

Characters and Unicode

Total characters22198
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2.0031958922501047
2nd row0.6770189176867532
3rd row-0.6491580568765987
4th row-0.6491580568765987
5th row-0.6491580568765987

Common Values

ValueCountFrequency (%)
-0.6491580568765987 778
65.4%
0.6770189176867532 267
 
22.4%
2.0031958922501047 94
 
7.9%
2.6662843795317808 51
 
4.3%

Length

2024-05-17T16:10:28.991309image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:29.174160image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.6491580568765987 778
65.4%
0.6770189176867532 267
 
22.4%
2.0031958922501047 94
 
7.9%
2.6662843795317808 51
 
4.3%

Most occurring characters

ValueCountFrequency (%)
6 3288
14.8%
8 3115
14.0%
5 2840
12.8%
7 2820
12.7%
0 2517
11.3%
9 2062
9.3%
1 1551
7.0%
. 1190
 
5.4%
4 923
 
4.2%
- 778
 
3.5%
Other values (2) 1114
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20230
91.1%
Other Punctuation 1190
 
5.4%
Dash Punctuation 778
 
3.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 3288
16.3%
8 3115
15.4%
5 2840
14.0%
7 2820
13.9%
0 2517
12.4%
9 2062
10.2%
1 1551
7.7%
4 923
 
4.6%
2 651
 
3.2%
3 463
 
2.3%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 778
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 22198
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 3288
14.8%
8 3115
14.0%
5 2840
12.8%
7 2820
12.7%
0 2517
11.3%
9 2062
9.3%
1 1551
7.0%
. 1190
 
5.4%
4 923
 
4.2%
- 778
 
3.5%
Other values (2) 1114
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22198
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 3288
14.8%
8 3115
14.0%
5 2840
12.8%
7 2820
12.7%
0 2517
11.3%
9 2062
9.3%
1 1551
7.0%
. 1190
 
5.4%
4 923
 
4.2%
- 778
 
3.5%
Other values (2) 1114
 
5.0%

STENOK_AN
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct8
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-2.3883789 × 10-17
Minimum-0.88156575
Maximum1.7055153
Zeros45
Zeros (%)3.8%
Negative736
Negative (%)61.8%
Memory size9.4 KiB
2024-05-17T16:10:29.336028image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum-0.88156575
5-th percentile-0.88156575
Q1-0.88156575
median-0.45038558
Q30.84315494
95-th percentile1.7055153
Maximum1.7055153
Range2.587081
Interquartile range (IQR)1.7247207

Descriptive statistics

Standard deviation1.0004204
Coefficient of variation (CV)-4.1887006 × 1016
Kurtosis-1.1147959
Mean-2.3883789 × 10-17
Median Absolute Deviation (MAD)0.43118017
Skewness0.68876546
Sum1.5987212 × 10-14
Variance1.000841
MonotonicityNot monotonic
2024-05-17T16:10:29.529247image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
-0.8815657493 524
44.0%
1.705515284 199
 
16.7%
-0.4503855772 119
 
10.0%
-0.01920540505 93
 
7.8%
1.274335111 79
 
6.6%
0.4119747671 77
 
6.5%
0.8431549392 54
 
4.5%
0 45
 
3.8%
ValueCountFrequency (%)
-0.8815657493 524
44.0%
-0.4503855772 119
 
10.0%
-0.01920540505 93
 
7.8%
0 45
 
3.8%
0.4119747671 77
 
6.5%
0.8431549392 54
 
4.5%
1.274335111 79
 
6.6%
1.705515284 199
 
16.7%
ValueCountFrequency (%)
1.705515284 199
 
16.7%
1.274335111 79
 
6.6%
0.8431549392 54
 
4.5%
0.4119747671 77
 
6.5%
0 45
 
3.8%
-0.01920540505 93
 
7.8%
-0.4503855772 119
 
10.0%
-0.8815657493 524
44.0%

FK_STENOK
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.70172 × 10-16
Minimum-1.0708901
Maximum2.767625
Zeros0
Zeros (%)0.0%
Negative564
Negative (%)47.4%
Memory size9.4 KiB
2024-05-17T16:10:29.687958image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum-1.0708901
5-th percentile-1.0708901
Q1-1.0708901
median0.84836745
Q30.84836745
95-th percentile0.84836745
Maximum2.767625
Range3.838515
Interquartile range (IQR)1.9192575

Descriptive statistics

Standard deviation1.0004204
Coefficient of variation (CV)5.878878 × 1015
Kurtosis-1.371168
Mean1.70172 × 10-16
Median Absolute Deviation (MAD)0.95962876
Skewness0.0912336
Sum2.4868996 × 10-13
Variance1.000841
MonotonicityNot monotonic
2024-05-17T16:10:29.844959image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0.8483674529 569
47.8%
-1.070890064 524
44.0%
-0.1112613053 40
 
3.4%
1.807996211 29
 
2.4%
2.130803885 × 10-1617
 
1.4%
2.767624969 11
 
0.9%
ValueCountFrequency (%)
-1.070890064 524
44.0%
-0.1112613053 40
 
3.4%
2.130803885 × 10-1617
 
1.4%
0.8483674529 569
47.8%
1.807996211 29
 
2.4%
2.767624969 11
 
0.9%
ValueCountFrequency (%)
2.767624969 11
 
0.9%
1.807996211 29
 
2.4%
0.8483674529 569
47.8%
2.130803885 × 10-1617
 
1.4%
-0.1112613053 40
 
3.4%
-1.070890064 524
44.0%

IBS_POST
Categorical

Distinct4
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
1.0895051205123867
468 
-0.1461022192257989
388 
-1.3817095589639845
328 
0.0
 
6

Length

Max length19
Median length19
Mean length18.52605
Min length3

Characters and Unicode

Total characters22046
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0895051205123867
2nd row-1.3817095589639845
3rd row1.0895051205123867
4th row1.0895051205123867
5th row1.0895051205123867

Common Values

ValueCountFrequency (%)
1.0895051205123867 468
39.3%
-0.1461022192257989 388
32.6%
-1.3817095589639845 328
27.6%
0.0 6
 
0.5%

Length

2024-05-17T16:10:30.099584image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:30.289794image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
1.0895051205123867 468
39.3%
0.1461022192257989 388
32.6%
1.3817095589639845 328
27.6%
0.0 6
 
0.5%

Most occurring characters

ValueCountFrequency (%)
1 3224
14.6%
5 2776
12.6%
9 2616
11.9%
0 2520
11.4%
2 2488
11.3%
8 2308
10.5%
. 1190
 
5.4%
6 1184
 
5.4%
7 1184
 
5.4%
3 1124
 
5.1%
Other values (2) 1432
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20140
91.4%
Other Punctuation 1190
 
5.4%
Dash Punctuation 716
 
3.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3224
16.0%
5 2776
13.8%
9 2616
13.0%
0 2520
12.5%
2 2488
12.4%
8 2308
11.5%
6 1184
 
5.9%
7 1184
 
5.9%
3 1124
 
5.6%
4 716
 
3.6%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 716
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 22046
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3224
14.6%
5 2776
12.6%
9 2616
11.9%
0 2520
11.4%
2 2488
11.3%
8 2308
10.5%
. 1190
 
5.4%
6 1184
 
5.4%
7 1184
 
5.4%
3 1124
 
5.1%
Other values (2) 1432
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22046
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3224
14.6%
5 2776
12.6%
9 2616
11.9%
0 2520
11.4%
2 2488
11.3%
8 2308
10.5%
. 1190
 
5.4%
6 1184
 
5.4%
7 1184
 
5.4%
3 1124
 
5.1%
Other values (2) 1432
6.5%

GB
Categorical

Distinct4
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size87.7 KiB
0.5949813244904116
626 
-1.2560716850353137
439 
1.5205078292532743
119 
-0.330545180272451
 
6

Length

Max length19
Median length18
Mean length18.368908
Min length18

Characters and Unicode

Total characters21859
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.5205078292532743
2nd row-1.2560716850353137
3rd row0.5949813244904116
4th row0.5949813244904116
5th row1.5205078292532743

Common Values

ValueCountFrequency (%)
0.5949813244904116 626
52.6%
-1.2560716850353137 439
36.9%
1.5205078292532743 119
 
10.0%
-0.330545180272451 6
 
0.5%

Length

2024-05-17T16:10:30.572298image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:30.816608image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.5949813244904116 626
52.6%
1.2560716850353137 439
36.9%
1.5205078292532743 119
 
10.0%
0.330545180272451 6
 
0.5%

Most occurring characters

ValueCountFrequency (%)
1 3326
15.2%
4 2635
12.1%
0 2386
10.9%
5 2318
10.6%
3 2193
10.0%
9 1997
9.1%
2 1553
7.1%
6 1504
6.9%
. 1190
 
5.4%
8 1190
 
5.4%
Other values (2) 1567
7.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20224
92.5%
Other Punctuation 1190
 
5.4%
Dash Punctuation 445
 
2.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3326
16.4%
4 2635
13.0%
0 2386
11.8%
5 2318
11.5%
3 2193
10.8%
9 1997
9.9%
2 1553
7.7%
6 1504
7.4%
8 1190
 
5.9%
7 1122
 
5.5%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 445
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 21859
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3326
15.2%
4 2635
12.1%
0 2386
10.9%
5 2318
10.6%
3 2193
10.0%
9 1997
9.1%
2 1553
7.1%
6 1504
6.9%
. 1190
 
5.4%
8 1190
 
5.4%
Other values (2) 1567
7.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21859
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3326
15.2%
4 2635
12.1%
0 2386
10.9%
5 2318
10.6%
3 2193
10.0%
9 1997
9.1%
2 1553
7.1%
6 1504
6.9%
. 1190
 
5.4%
8 1190
 
5.4%
Other values (2) 1567
7.2%

SIM_GIPERT
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:31.024266image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:31.254943image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

ZSN_A
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:31.433634image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:31.572976image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

nr_11
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:31.725380image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:31.867296image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

nr_01
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:32.050677image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:32.188714image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

nr_02
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:32.333633image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:32.468901image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

nr_03
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:32.616261image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:32.778165image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

nr_04
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:32.929119image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:33.075091image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

nr_07
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:33.222197image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:33.363831image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

nr_08
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:33.542778image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:33.691922image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

np_01
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:33.871442image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:34.015539image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

np_04
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:34.208249image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:34.340541image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

np_05
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:34.497372image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:34.653577image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

np_07
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:34.830449image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:34.979445image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

np_08
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:35.158635image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:35.298217image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

np_09
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:35.444223image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:35.618244image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

np_10
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:35.757923image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:35.891881image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

endocr_01
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:36.041591image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:36.215861image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

endocr_02
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:36.376694image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:36.529048image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

endocr_03
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:36.671191image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:36.844149image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

zab_leg_01
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:37.004145image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:37.140144image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

zab_leg_02
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:37.289865image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:37.428166image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

zab_leg_03
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:37.608056image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:37.752636image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

zab_leg_04
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:37.908123image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:38.045124image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

zab_leg_06
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:38.196843image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:38.364226image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

O_L_POST
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:38.541323image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:38.713511image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

K_SH_POST
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:38.864518image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:39.034748image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

MP_TP_POST
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:39.523898image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:39.673717image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

SVT_POST
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:39.855387image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:40.004604image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

GT_POST
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:40.168783image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:40.427622image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

FIB_G_POST
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:40.650592image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:40.889076image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

ant_im
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct6
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-1.1941895 × 10-17
Minimum-0.90727357
Maximum1.553812
Zeros29
Zeros (%)2.4%
Negative793
Negative (%)66.6%
Memory size9.4 KiB
2024-05-17T16:10:41.051882image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum-0.90727357
5-th percentile-0.90727357
Q1-0.90727357
median-0.29200218
Q31.553812
95-th percentile1.553812
Maximum1.553812
Range2.4610855
Interquartile range (IQR)2.4610855

Descriptive statistics

Standard deviation1.0004204
Coefficient of variation (CV)-8.3774012 × 1016
Kurtosis-1.1817296
Mean-1.1941895 × 10-17
Median Absolute Deviation (MAD)0.61527139
Skewness0.70693453
Sum5.6843419 × 10-14
Variance1.000841
MonotonicityNot monotonic
2024-05-17T16:10:41.336953image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
-0.9072735693 465
39.1%
-0.2920021827 328
27.6%
1.553811977 314
26.4%
0.323269204 34
 
2.9%
0 29
 
2.4%
0.9385405907 20
 
1.7%
ValueCountFrequency (%)
-0.9072735693 465
39.1%
-0.2920021827 328
27.6%
0 29
 
2.4%
0.323269204 34
 
2.9%
0.9385405907 20
 
1.7%
1.553811977 314
26.4%
ValueCountFrequency (%)
1.553811977 314
26.4%
0.9385405907 20
 
1.7%
0.323269204 34
 
2.9%
0 29
 
2.4%
-0.2920021827 328
27.6%
-0.9072735693 465
39.1%

lat_im
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size87.8 KiB
0.3154952196459622
621 
-1.1214869135852568
418 
2.4709684194927903
70 
1.7524773528771809
 
57
-1.5953706502882735e-16
 
24

Length

Max length23
Median length18
Mean length18.452101
Min length18

Characters and Unicode

Total characters21958
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row-1.1214869135852568
2nd row0.3154952196459622
3rd row0.3154952196459622
4th row0.3154952196459622
5th row0.3154952196459622

Common Values

ValueCountFrequency (%)
0.3154952196459622 621
52.2%
-1.1214869135852568 418
35.1%
2.4709684194927903 70
 
5.9%
1.7524773528771809 57
 
4.8%
-1.5953706502882735e-16 24
 
2.0%

Length

2024-05-17T16:10:41.517253image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:41.686207image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.3154952196459622 621
52.2%
1.1214869135852568 418
35.1%
2.4709684194927903 70
 
5.9%
1.7524773528771809 57
 
4.8%
1.5953706502882735e-16 24
 
2.0%

Most occurring characters

ValueCountFrequency (%)
5 3327
15.2%
1 3146
14.3%
2 3001
13.7%
9 2642
12.0%
6 2196
10.0%
4 1927
8.8%
8 1486
6.8%
3 1214
 
5.5%
. 1190
 
5.4%
0 866
 
3.9%
Other values (3) 963
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20278
92.3%
Other Punctuation 1190
 
5.4%
Dash Punctuation 466
 
2.1%
Lowercase Letter 24
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 3327
16.4%
1 3146
15.5%
2 3001
14.8%
9 2642
13.0%
6 2196
10.8%
4 1927
9.5%
8 1486
7.3%
3 1214
 
6.0%
0 866
 
4.3%
7 473
 
2.3%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 466
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 21934
99.9%
Latin 24
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
5 3327
15.2%
1 3146
14.3%
2 3001
13.7%
9 2642
12.0%
6 2196
10.0%
4 1927
8.8%
8 1486
6.8%
3 1214
 
5.5%
. 1190
 
5.4%
0 866
 
3.9%
Other values (2) 939
 
4.3%
Latin
ValueCountFrequency (%)
e 24
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21958
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 3327
15.2%
1 3146
14.3%
2 3001
13.7%
9 2642
12.0%
6 2196
10.0%
4 1927
8.8%
8 1486
6.8%
3 1214
 
5.5%
. 1190
 
5.4%
0 866
 
3.9%
Other values (3) 963
 
4.4%

inf_im
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-7.3260709 × 10-17
Minimum-0.70950429
Maximum2.2904649
Zeros0
Zeros (%)0.0%
Negative709
Negative (%)59.6%
Memory size9.4 KiB
2024-05-17T16:10:41.852396image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum-0.70950429
5-th percentile-0.70950429
Q1-0.70950429
median-0.70950429
Q30.79048032
95-th percentile2.2904649
Maximum2.2904649
Range2.9999692
Interquartile range (IQR)1.4999846

Descriptive statistics

Standard deviation1.0004204
Coefficient of variation (CV)-1.365562 × 1016
Kurtosis0.067631251
Mean-7.3260709 × 10-17
Median Absolute Deviation (MAD)0
Skewness1.1897376
Sum-1.1368684 × 10-13
Variance1.000841
MonotonicityNot monotonic
2024-05-17T16:10:42.000098image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
-0.7095042878 686
57.6%
0.04048801642 156
 
13.1%
0.7904803207 134
 
11.3%
2.290464929 107
 
9.0%
1.540472625 84
 
7.1%
-8.326587245 × 10-1723
 
1.9%
ValueCountFrequency (%)
-0.7095042878 686
57.6%
-8.326587245 × 10-1723
 
1.9%
0.04048801642 156
 
13.1%
0.7904803207 134
 
11.3%
1.540472625 84
 
7.1%
2.290464929 107
 
9.0%
ValueCountFrequency (%)
2.290464929 107
 
9.0%
1.540472625 84
 
7.1%
0.7904803207 134
 
11.3%
0.04048801642 156
 
13.1%
-8.326587245 × 10-1723
 
1.9%
-0.7095042878 686
57.6%

post_im
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:42.187202image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:42.326890image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

IM_PG_P
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:42.474861image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:42.626974image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

n_r_ecg_p_01
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:42.773863image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:42.910443image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

n_r_ecg_p_02
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:43.069972image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:43.229993image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

n_r_ecg_p_03
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:43.387638image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:43.525639image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

n_r_ecg_p_04
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:43.685105image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:43.839420image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

n_r_ecg_p_05
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:43.989009image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:44.137913image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

n_r_ecg_p_06
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:44.288579image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:44.436369image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

n_r_ecg_p_08
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:44.601159image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:44.739583image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

n_r_ecg_p_09
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:44.890220image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:45.038267image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

n_r_ecg_p_10
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:45.188813image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:45.329523image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

n_p_ecg_p_01
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:45.473495image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:45.616495image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

n_p_ecg_p_03
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:45.762496image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:45.906969image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

n_p_ecg_p_04
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:46.064048image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:46.198051image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

n_p_ecg_p_05
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:46.348980image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:46.487757image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

n_p_ecg_p_06
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:46.641216image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:46.782642image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

n_p_ecg_p_07
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:46.934554image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:47.075571image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

n_p_ecg_p_08
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:47.225637image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:47.363752image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

n_p_ecg_p_09
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:47.534075image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:47.678979image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

n_p_ecg_p_10
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:47.824593image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:47.958002image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

n_p_ecg_p_11
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:48.103004image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:48.246769image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

n_p_ecg_p_12
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:48.399337image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:48.538259image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

fibr_ter_01
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:48.696089image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:48.833115image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

fibr_ter_02
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:48.986010image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:49.126492image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

fibr_ter_03
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:49.295431image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:49.441786image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

fibr_ter_05
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:49.590298image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:49.730010image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

fibr_ter_06
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:49.892700image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:50.029702image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

fibr_ter_07
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:50.174294image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:50.321381image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

fibr_ter_08
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:50.475950image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:50.625664image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

L_BLOOD
Real number (ℝ)

ZEROS 

Distinct125
Distinct (%)10.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-1.4516866 × 10-16
Minimum-2.2595641
Maximum2.5848866
Zeros71
Zeros (%)6.0%
Negative656
Negative (%)55.1%
Memory size9.4 KiB
2024-05-17T16:10:50.797773image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum-2.2595641
5-th percentile-1.3468415
Q1-0.71495663
median-0.15328118
Q30.51370841
95-th percentile2.1285253
Maximum2.5848866
Range4.8444507
Interquartile range (IQR)1.228665

Descriptive statistics

Standard deviation1.0004204
Coefficient of variation (CV)-6.8914354 × 1015
Kurtosis0.20466199
Mean-1.4516866 × 10-16
Median Absolute Deviation (MAD)0.63188488
Skewness0.78112863
Sum-1.9895197 × 10-13
Variance1.000841
MonotonicityNot monotonic
2024-05-17T16:10:51.019429image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 71
 
6.0%
2.584886628 41
 
3.4%
-0.5745377653 24
 
2.0%
-0.4341189033 23
 
1.9%
-0.1532811795 23
 
1.9%
-0.8553754891 22
 
1.8%
-1.206422644 22
 
1.8%
-0.3990141879 21
 
1.8%
-0.7149566272 21
 
1.8%
-0.5043283343 21
 
1.8%
Other values (115) 901
75.7%
ValueCountFrequency (%)
-2.259564108 1
 
0.1%
-2.224459393 1
 
0.1%
-1.838307523 2
 
0.2%
-1.768098092 1
 
0.1%
-1.732993376 1
 
0.1%
-1.697888661 1
 
0.1%
-1.662783945 1
 
0.1%
-1.62767923 2
 
0.2%
-1.592574514 2
 
0.2%
-1.557469799 9
0.8%
ValueCountFrequency (%)
2.584886628 41
3.4%
2.549781913 2
 
0.2%
2.479572482 1
 
0.1%
2.444467766 3
 
0.3%
2.409363051 2
 
0.2%
2.374258335 1
 
0.1%
2.268944189 1
 
0.1%
2.233839473 2
 
0.2%
2.198734758 3
 
0.3%
2.163630042 3
 
0.3%

TIME_B_S
Real number (ℝ)

ZEROS 

Distinct10
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.9640184 × 10-17
Minimum-1.4053356
Maximum1.4330492
Zeros89
Zeros (%)7.5%
Negative533
Negative (%)44.8%
Memory size9.4 KiB
2024-05-17T16:10:51.177454image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum-1.4053356
5-th percentile-1.4053356
Q1-1.0505375
median0
Q31.0782511
95-th percentile1.4330492
Maximum1.4330492
Range2.8383848
Interquartile range (IQR)2.1287886

Descriptive statistics

Standard deviation1.0004204
Coefficient of variation (CV)1.0040331 × 1016
Kurtosis-1.4233457
Mean9.9640184 × 10-17
Median Absolute Deviation (MAD)1.0505375
Skewness0.11824882
Sum1.1368684 × 10-13
Variance1.000841
MonotonicityNot monotonic
2024-05-17T16:10:51.327288image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
-1.05053752 237
19.9%
1.433049188 223
18.7%
-1.405335621 124
10.4%
0.7234529856 117
9.8%
-0.6957394191 116
9.7%
0.3686548844 98
8.2%
0 89
 
7.5%
1.078251087 76
 
6.4%
-0.3409413179 56
 
4.7%
0.01385678324 54
 
4.5%
ValueCountFrequency (%)
-1.405335621 124
10.4%
-1.05053752 237
19.9%
-0.6957394191 116
9.7%
-0.3409413179 56
 
4.7%
0 89
 
7.5%
0.01385678324 54
 
4.5%
0.3686548844 98
8.2%
0.7234529856 117
9.8%
1.078251087 76
 
6.4%
1.433049188 223
18.7%
ValueCountFrequency (%)
1.433049188 223
18.7%
1.078251087 76
 
6.4%
0.7234529856 117
9.8%
0.3686548844 98
8.2%
0.01385678324 54
 
4.5%
0 89
 
7.5%
-0.3409413179 56
 
4.7%
-0.6957394191 116
9.7%
-1.05053752 237
19.9%
-1.405335621 124
10.4%

R_AB_1_n
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:51.500838image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:51.634788image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

R_AB_2_n
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:51.785088image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:51.923496image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

R_AB_3_n
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:52.069913image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:52.208879image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

NITR_S
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:52.687879image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:52.820880image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

NA_R_1_n
Categorical

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size88.0 KiB
-0.5892758442036962
836 
0.9548089837649293
259 
2.498893811733555
 
72
3.2709362257178674
 
20
0.0
 
3

Length

Max length19
Median length19
Mean length18.604202
Min length3

Characters and Unicode

Total characters22139
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row-0.5892758442036962
2nd row-0.5892758442036962
3rd row0.9548089837649293
4th row-0.5892758442036962
5th row-0.5892758442036962

Common Values

ValueCountFrequency (%)
-0.5892758442036962 836
70.3%
0.9548089837649293 259
 
21.8%
2.498893811733555 72
 
6.1%
3.2709362257178674 20
 
1.7%
0.0 3
 
0.3%

Length

2024-05-17T16:10:52.990374image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:53.156411image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.5892758442036962 836
70.3%
0.9548089837649293 259
 
21.8%
2.498893811733555 72
 
6.1%
3.2709362257178674 20
 
1.7%
0.0 3
 
0.3%

Most occurring characters

ValueCountFrequency (%)
2 2899
13.1%
9 2872
13.0%
8 2685
12.1%
4 2282
10.3%
0 2216
10.0%
5 2167
9.8%
6 1971
8.9%
3 1610
7.3%
7 1247
5.6%
. 1190
5.4%
Other values (2) 1000
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20113
90.8%
Other Punctuation 1190
 
5.4%
Dash Punctuation 836
 
3.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 2899
14.4%
9 2872
14.3%
8 2685
13.3%
4 2282
11.3%
0 2216
11.0%
5 2167
10.8%
6 1971
9.8%
3 1610
8.0%
7 1247
6.2%
1 164
 
0.8%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 836
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 22139
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 2899
13.1%
9 2872
13.0%
8 2685
12.1%
4 2282
10.3%
0 2216
10.0%
5 2167
9.8%
6 1971
8.9%
3 1610
7.3%
7 1247
5.6%
. 1190
5.4%
Other values (2) 1000
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22139
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 2899
13.1%
9 2872
13.0%
8 2685
12.1%
4 2282
10.3%
0 2216
10.0%
5 2167
9.8%
6 1971
8.9%
3 1610
7.3%
7 1247
5.6%
. 1190
5.4%
Other values (2) 1000
 
4.5%

NA_R_2_n
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:53.344625image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:53.485072image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

NA_R_3_n
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:53.660094image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:53.804666image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

NOT_NA_1_n
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size88.0 KiB
-0.5646627658731139
860 
1.1532457772838565
269 
2.871154320440827
 
39
3.7301085920193127
 
17
0.0
 
5

Length

Max length19
Median length19
Mean length18.626891
Min length3

Characters and Unicode

Total characters22166
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row-0.5646627658731139
2nd row1.1532457772838565
3rd row3.7301085920193127
4th row-0.5646627658731139
5th row-0.5646627658731139

Common Values

ValueCountFrequency (%)
-0.5646627658731139 860
72.3%
1.1532457772838565 269
 
22.6%
2.871154320440827 39
 
3.3%
3.7301085920193127 17
 
1.4%
0.0 5
 
0.4%

Length

2024-05-17T16:10:53.968725image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:54.149098image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.5646627658731139 860
72.3%
1.1532457772838565 269
 
22.6%
2.871154320440827 39
 
3.3%
3.7301085920193127 17
 
1.4%
0.0 5
 
0.4%

Most occurring characters

ValueCountFrequency (%)
6 3709
16.7%
5 2852
12.9%
7 2639
11.9%
1 2387
10.8%
3 2348
10.6%
2 1549
7.0%
8 1493
6.7%
4 1246
 
5.6%
. 1190
 
5.4%
0 999
 
4.5%
Other values (2) 1754
7.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20116
90.8%
Other Punctuation 1190
 
5.4%
Dash Punctuation 860
 
3.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 3709
18.4%
5 2852
14.2%
7 2639
13.1%
1 2387
11.9%
3 2348
11.7%
2 1549
7.7%
8 1493
7.4%
4 1246
 
6.2%
0 999
 
5.0%
9 894
 
4.4%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 860
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 22166
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 3709
16.7%
5 2852
12.9%
7 2639
11.9%
1 2387
10.8%
3 2348
10.6%
2 1549
7.0%
8 1493
6.7%
4 1246
 
5.6%
. 1190
 
5.4%
0 999
 
4.5%
Other values (2) 1754
7.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22166
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 3709
16.7%
5 2852
12.9%
7 2639
11.9%
1 2387
10.8%
3 2348
10.6%
2 1549
7.0%
8 1493
6.7%
4 1246
 
5.6%
. 1190
 
5.4%
0 999
 
4.5%
Other values (2) 1754
7.9%

NOT_NA_2_n
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:54.335528image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:54.475705image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

NOT_NA_3_n
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:54.627249image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:54.766479image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

LID_S_n
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size88.1 KiB
-0.6290722049644462
849 
1.5990488084275891
334 
-1.2368556253594872e-16
 
7

Length

Max length23
Median length19
Mean length18.742857
Min length18

Characters and Unicode

Total characters22304
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.5990488084275891
2nd row1.5990488084275891
3rd row1.5990488084275891
4th row-0.6290722049644462
5th row-0.6290722049644462

Common Values

ValueCountFrequency (%)
-0.6290722049644462 849
71.3%
1.5990488084275891 334
 
28.1%
-1.2368556253594872e-16 7
 
0.6%

Length

2024-05-17T16:10:54.931992image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:55.089874image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.6290722049644462 849
71.3%
1.5990488084275891 334
 
28.1%
1.2368556253594872e-16 7
 
0.6%

Most occurring characters

ValueCountFrequency (%)
4 4071
18.3%
2 3751
16.8%
0 3215
14.4%
9 2707
12.1%
6 2568
11.5%
8 1350
 
6.1%
. 1190
 
5.3%
7 1190
 
5.3%
- 863
 
3.9%
5 696
 
3.1%
Other values (3) 703
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20244
90.8%
Other Punctuation 1190
 
5.3%
Dash Punctuation 863
 
3.9%
Lowercase Letter 7
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 4071
20.1%
2 3751
18.5%
0 3215
15.9%
9 2707
13.4%
6 2568
12.7%
8 1350
 
6.7%
7 1190
 
5.9%
5 696
 
3.4%
1 682
 
3.4%
3 14
 
0.1%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 863
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 22297
> 99.9%
Latin 7
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
4 4071
18.3%
2 3751
16.8%
0 3215
14.4%
9 2707
12.1%
6 2568
11.5%
8 1350
 
6.1%
. 1190
 
5.3%
7 1190
 
5.3%
- 863
 
3.9%
5 696
 
3.1%
Other values (2) 696
 
3.1%
Latin
ValueCountFrequency (%)
e 7
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22304
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 4071
18.3%
2 3751
16.8%
0 3215
14.4%
9 2707
12.1%
6 2568
11.5%
8 1350
 
6.1%
. 1190
 
5.3%
7 1190
 
5.3%
- 863
 
3.9%
5 696
 
3.1%
Other values (3) 703
 
3.2%

B_BLOK_S_n
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:55.262525image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:55.401828image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

ANT_CA_S_n
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size87.6 KiB
0.6369309242379417
842 
-1.5819936230334724
339 
-2.463501122286675e-16
 
9

Length

Max length22
Median length18
Mean length18.315126
Min length18

Characters and Unicode

Total characters21795
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row-1.5819936230334724
2nd row0.6369309242379417
3rd row-1.5819936230334724
4th row0.6369309242379417
5th row0.6369309242379417

Common Values

ValueCountFrequency (%)
0.6369309242379417 842
70.8%
-1.5819936230334724 339
28.5%
-2.463501122286675e-16 9
 
0.8%

Length

2024-05-17T16:10:55.570762image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:55.740878image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.6369309242379417 842
70.8%
1.5819936230334724 339
28.5%
2.463501122286675e-16 9
 
0.8%

Most occurring characters

ValueCountFrequency (%)
3 3891
17.9%
9 3204
14.7%
2 2398
11.0%
4 2371
10.9%
6 2059
9.4%
0 2032
9.3%
7 2032
9.3%
1 1547
 
7.1%
. 1190
 
5.5%
- 357
 
1.6%
Other values (3) 714
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20239
92.9%
Other Punctuation 1190
 
5.5%
Dash Punctuation 357
 
1.6%
Lowercase Letter 9
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 3891
19.2%
9 3204
15.8%
2 2398
11.8%
4 2371
11.7%
6 2059
10.2%
0 2032
10.0%
7 2032
10.0%
1 1547
 
7.6%
5 357
 
1.8%
8 348
 
1.7%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 357
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 21786
> 99.9%
Latin 9
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
3 3891
17.9%
9 3204
14.7%
2 2398
11.0%
4 2371
10.9%
6 2059
9.5%
0 2032
9.3%
7 2032
9.3%
1 1547
 
7.1%
. 1190
 
5.5%
- 357
 
1.6%
Other values (2) 705
 
3.2%
Latin
ValueCountFrequency (%)
e 9
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21795
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 3891
17.9%
9 3204
14.7%
2 2398
11.0%
4 2371
10.9%
6 2059
9.4%
0 2032
9.3%
7 2032
9.3%
1 1547
 
7.1%
. 1190
 
5.5%
- 357
 
1.6%
Other values (3) 714
 
3.3%

GEPAR_S_n
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size86.2 KiB
0.642183732540724
836 
-1.57438592493855
341 
-2.4608866694189867e-16
 
13

Length

Max length23
Median length17
Mean length17.065546
Min length17

Characters and Unicode

Total characters20308
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.642183732540724
2nd row0.642183732540724
3rd row0.642183732540724
4th row0.642183732540724
5th row-1.57438592493855

Common Values

ValueCountFrequency (%)
0.642183732540724 836
70.3%
-1.57438592493855 341
28.7%
-2.4608866694189867e-16 13
 
1.1%

Length

2024-05-17T16:10:55.927714image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:56.088635image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.642183732540724 836
70.3%
1.57438592493855 341
28.7%
2.4608866694189867e-16 13
 
1.1%

Most occurring characters

ValueCountFrequency (%)
4 3216
15.8%
2 2862
14.1%
3 2354
11.6%
5 2200
10.8%
7 2026
10.0%
0 1685
8.3%
8 1570
7.7%
1 1203
 
5.9%
. 1190
 
5.9%
6 914
 
4.5%
Other values (3) 1088
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18738
92.3%
Other Punctuation 1190
 
5.9%
Dash Punctuation 367
 
1.8%
Lowercase Letter 13
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 3216
17.2%
2 2862
15.3%
3 2354
12.6%
5 2200
11.7%
7 2026
10.8%
0 1685
9.0%
8 1570
8.4%
1 1203
 
6.4%
6 914
 
4.9%
9 708
 
3.8%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 367
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 20295
99.9%
Latin 13
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
4 3216
15.8%
2 2862
14.1%
3 2354
11.6%
5 2200
10.8%
7 2026
10.0%
0 1685
8.3%
8 1570
7.7%
1 1203
 
5.9%
. 1190
 
5.9%
6 914
 
4.5%
Other values (2) 1075
 
5.3%
Latin
ValueCountFrequency (%)
e 13
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20308
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 3216
15.8%
2 2862
14.1%
3 2354
11.6%
5 2200
10.8%
7 2026
10.0%
0 1685
8.3%
8 1570
7.7%
1 1203
 
5.9%
. 1190
 
5.9%
6 914
 
4.5%
Other values (3) 1088
 
5.4%

ASP_S_n
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:56.259818image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:56.395602image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

TIKL_S_n
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:56.540603image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:56.686211image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

TRENT_S_n
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.9 KiB
0.0
1190 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3570
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 1190
100.0%

Length

2024-05-17T16:10:56.849120image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-17T16:10:56.986645image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1190
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
66.7%
Other Punctuation 1190
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2380
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2380
66.7%
. 1190
33.3%

Interactions

2024-05-17T16:10:24.566568image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-17T16:10:17.485813image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-17T16:10:18.744496image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-17T16:10:19.906982image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-17T16:10:21.145498image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-17T16:10:22.265610image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-17T16:10:23.390499image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-17T16:10:24.754642image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-17T16:10:17.663839image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-17T16:10:18.914376image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-17T16:10:20.119186image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-17T16:10:21.282416image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-17T16:10:22.417546image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-17T16:10:23.542525image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-17T16:10:24.913517image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-17T16:10:17.877216image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-17T16:10:19.073162image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-17T16:10:20.303914image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-17T16:10:21.466983image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-17T16:10:22.588140image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-17T16:10:23.711574image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-17T16:10:25.109462image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-17T16:10:18.060773image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-17T16:10:19.262862image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-17T16:10:20.471369image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-17T16:10:21.624593image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-17T16:10:22.789432image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-17T16:10:23.907685image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-17T16:10:25.260608image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-17T16:10:18.255857image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-17T16:10:19.421244image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-17T16:10:20.631411image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-17T16:10:21.774665image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-17T16:10:22.940085image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-17T16:10:24.057575image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-17T16:10:25.415259image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-17T16:10:18.420415image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-17T16:10:19.594702image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-17T16:10:20.823044image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-17T16:10:21.923302image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-17T16:10:23.084983image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-17T16:10:24.250762image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-17T16:10:25.609313image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-17T16:10:18.576749image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-17T16:10:19.756639image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-17T16:10:20.978117image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-17T16:10:22.114821image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-17T16:10:23.230990image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-17T16:10:24.391424image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Correlations

2024-05-17T16:10:57.104157image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
AGEANT_CA_S_nFK_STENOKGBGEPAR_S_nIBS_POSTINF_ANAMLID_S_nL_BLOODNA_R_1_nNOT_NA_1_nSEXSTENOK_ANTIME_B_Sant_iminf_imlat_im
AGE1.0000.0220.2010.1070.0660.1170.0800.000-0.0270.0000.0000.3840.2120.028-0.0240.0130.059
ANT_CA_S_n0.0221.0000.0230.0550.5240.0340.0000.5340.0140.4070.5260.0380.0170.020-0.058-0.0070.000
FK_STENOK0.2010.0231.0000.0590.0000.4490.1980.044-0.0400.0000.0000.0970.8650.041-0.015-0.0130.022
GB0.1070.0550.0591.0000.0000.0730.0550.037-0.0210.0330.0000.2380.1180.044-0.021-0.0080.070
GEPAR_S_n0.0660.5240.0000.0001.0000.0510.0000.4450.0490.3450.4350.049-0.012-0.156-0.0020.0630.000
IBS_POST0.1170.0340.4490.0730.0511.0000.1720.069-0.0970.0160.0000.0830.3080.0860.018-0.0780.044
INF_ANAM0.0800.0000.1980.0550.0000.1721.0000.075-0.0240.0800.0000.0230.318-0.059-0.053-0.0110.101
LID_S_n0.0000.5340.0440.0370.4450.0690.0751.0000.0790.4930.5980.090-0.063-0.1790.0730.0660.081
L_BLOOD-0.0270.014-0.040-0.0210.049-0.097-0.0240.0791.0000.0760.0000.000-0.043-0.1150.0140.0330.071
NA_R_1_n0.0000.4070.0000.0330.3450.0160.0800.4930.0761.0000.3900.0000.063-0.2330.0120.0840.063
NOT_NA_1_n0.0000.5260.0000.0000.4350.0000.0000.5980.0000.3901.0000.0920.013-0.1040.043-0.0140.037
SEX0.3840.0380.0970.2380.0490.0830.0230.0900.0000.0000.0921.000-0.089-0.026-0.0180.0410.048
STENOK_AN0.2120.0170.8650.118-0.0120.3080.318-0.063-0.0430.0630.013-0.0891.0000.035-0.0450.0060.043
TIME_B_S0.0280.0200.0410.044-0.1560.086-0.059-0.179-0.115-0.233-0.104-0.0260.0351.0000.051-0.0970.080
ant_im-0.024-0.058-0.015-0.021-0.0020.018-0.0530.0730.0140.0120.043-0.018-0.0450.0511.000-0.7080.559
inf_im0.013-0.007-0.013-0.0080.063-0.078-0.0110.0660.0330.084-0.0140.0410.006-0.097-0.7081.0000.309
lat_im0.0590.0000.0220.0700.0000.0440.1010.0810.0710.0630.0370.0480.0430.0800.5590.3091.000

Missing values

2024-05-17T16:10:26.456491image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-17T16:10:27.273710image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

AGESEXINF_ANAMSTENOK_ANFK_STENOKIBS_POSTGBSIM_GIPERTZSN_Anr_11nr_01nr_02nr_03nr_04nr_07nr_08np_01np_04np_05np_07np_08np_09np_10endocr_01endocr_02endocr_03zab_leg_01zab_leg_02zab_leg_03zab_leg_04zab_leg_06O_L_POSTK_SH_POSTMP_TP_POSTSVT_POSTGT_POSTFIB_G_POSTant_imlat_iminf_impost_imIM_PG_Pn_r_ecg_p_01n_r_ecg_p_02n_r_ecg_p_03n_r_ecg_p_04n_r_ecg_p_05n_r_ecg_p_06n_r_ecg_p_08n_r_ecg_p_09n_r_ecg_p_10n_p_ecg_p_01n_p_ecg_p_03n_p_ecg_p_04n_p_ecg_p_05n_p_ecg_p_06n_p_ecg_p_07n_p_ecg_p_08n_p_ecg_p_09n_p_ecg_p_10n_p_ecg_p_11n_p_ecg_p_12fibr_ter_01fibr_ter_02fibr_ter_03fibr_ter_05fibr_ter_06fibr_ter_07fibr_ter_08L_BLOODTIME_B_SR_AB_1_nR_AB_2_nR_AB_3_nNITR_SNA_R_1_nNA_R_2_nNA_R_3_nNOT_NA_1_nNOT_NA_2_nNOT_NA_3_nLID_S_nB_BLOK_S_nANT_CA_S_nGEPAR_S_nASP_S_nTIKL_S_nTRENT_S_n
01.4961410.7088902.003196-0.450386-0.1112611.0895051.5205080.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0-0.292002-1.121487-0.7095040.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0-0.153281-0.3409410.00.00.00.0-0.5892760.00.0-0.5646630.00.01.5990490.0-1.5819946.421837e-010.00.00.0
1-0.4758080.7088900.677019-0.881566-1.070890-1.381710-1.2560720.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.5538120.315495-0.7095040.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0-0.223491-1.0505380.00.00.00.0-0.5892760.00.01.1532460.00.01.5990490.00.6369316.421837e-010.00.00.0
2-0.7447100.708890-0.649158-0.881566-1.0708901.0895050.5949810.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.5538120.315495-0.7095040.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.829651-0.6957390.00.00.00.00.9548090.00.03.7301090.00.01.5990490.0-1.5819946.421837e-010.00.00.0
30.689435-1.410656-0.649158-0.881566-1.0708901.0895050.5949810.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0-0.9072740.3154950.0404880.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.000000-1.0505380.00.00.00.0-0.5892760.00.0-0.5646630.00.0-0.6290720.00.6369316.421837e-010.00.00.0
4-0.0276380.708890-0.649158-0.881566-1.0708901.0895051.5205080.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.5538120.315495-0.7095040.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0-0.0479671.4330490.00.00.00.0-0.5892760.00.0-0.5646630.00.0-0.6290720.00.636931-1.574386e+000.00.00.0
50.3308980.708890-0.649158-0.4503860.848367-0.146102-1.2560720.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0-0.2920020.315495-0.7095040.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0-0.434119-1.0505380.00.00.00.0-0.5892760.00.0-0.5646630.00.0-0.6290720.0-1.5819946.421837e-010.00.00.0
60.8687030.7088900.677019-0.4503860.848367-0.1461020.5949810.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0-0.907274-1.1214871.5404730.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.934965-1.4053360.00.00.00.0-0.5892760.00.0-0.5646630.00.0-0.6290720.0-1.5819946.421837e-010.00.00.0
70.4205320.708890-0.649158-0.450386-0.1112611.0895050.5949810.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0-0.907274-1.1214870.7904800.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0-0.7851660.7234530.00.00.00.0-0.5892760.00.0-0.5646630.00.0-0.6290720.00.6369316.421837e-010.00.00.0
8-0.0276380.708890-0.649158-0.881566-1.0708901.0895050.5949810.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0-0.907274-1.1214871.5404730.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0-0.785166-0.6957390.00.00.00.00.9548090.00.0-0.5646630.00.01.5990490.0-1.581994-2.460887e-160.00.00.0
91.496141-1.4106562.003196-0.881566-1.070890-1.3817101.5205080.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.5538120.315495-0.7095040.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0-0.539433-0.6957390.00.00.00.0-0.5892760.00.01.1532460.00.0-0.6290720.00.636931-1.574386e+000.00.00.0
AGESEXINF_ANAMSTENOK_ANFK_STENOKIBS_POSTGBSIM_GIPERTZSN_Anr_11nr_01nr_02nr_03nr_04nr_07nr_08np_01np_04np_05np_07np_08np_09np_10endocr_01endocr_02endocr_03zab_leg_01zab_leg_02zab_leg_03zab_leg_04zab_leg_06O_L_POSTK_SH_POSTMP_TP_POSTSVT_POSTGT_POSTFIB_G_POSTant_imlat_iminf_impost_imIM_PG_Pn_r_ecg_p_01n_r_ecg_p_02n_r_ecg_p_03n_r_ecg_p_04n_r_ecg_p_05n_r_ecg_p_06n_r_ecg_p_08n_r_ecg_p_09n_r_ecg_p_10n_p_ecg_p_01n_p_ecg_p_03n_p_ecg_p_04n_p_ecg_p_05n_p_ecg_p_06n_p_ecg_p_07n_p_ecg_p_08n_p_ecg_p_09n_p_ecg_p_10n_p_ecg_p_11n_p_ecg_p_12fibr_ter_01fibr_ter_02fibr_ter_03fibr_ter_05fibr_ter_06fibr_ter_07fibr_ter_08L_BLOODTIME_B_SR_AB_1_nR_AB_2_nR_AB_3_nNITR_SNA_R_1_nNA_R_2_nNA_R_3_nNOT_NA_1_nNOT_NA_2_nNOT_NA_3_nLID_S_nB_BLOK_S_nANT_CA_S_nGEPAR_S_nASP_S_nTIKL_S_nTRENT_S_n
11800.151630-1.410656-0.649158-0.0192050.848367-0.1461020.5949810.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.000000-1.595371e-16-8.326587e-170.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0-1.206423-0.3409410.00.00.00.0-0.5892760.00.0-0.5646630.00.01.5990490.00.6369310.6421840.00.00.0
11811.854677-1.410656-0.6491580.0000001.807996-0.146102-1.2560720.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0-0.907274-1.121487e+002.290465e+000.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.7594410.7234530.00.00.00.00.9548090.00.0-0.5646630.00.01.5990490.00.636931-1.5743860.00.00.0
11821.406507-1.410656-0.649158-0.881566-1.0708901.0895050.5949810.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0-0.907274-1.121487e+002.290465e+000.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.4083941.0782510.00.00.00.00.9548090.00.0-0.5646630.00.01.5990490.00.636931-1.5743860.00.00.0
11830.5998010.7088900.677019-0.0192050.848367-0.1461021.5205080.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0-0.9072743.154952e-012.290465e+000.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0-0.679852-1.0505380.00.00.00.00.9548090.00.0-0.5646630.00.01.5990490.0-1.5819940.6421840.00.00.0
1184-0.5654420.708890-0.649158-0.881566-1.070890-1.3817100.5949810.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0-0.9072743.154952e-017.904803e-010.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.1977661.0782510.00.00.00.00.9548090.00.0-0.5646630.00.01.5990490.00.636931-1.5743860.00.00.0
11851.5857750.708890-0.649158-0.881566-1.070890-1.381710-1.2560720.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.5538121.752477e+00-7.095043e-010.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0-0.083072-0.6957390.00.00.00.0-0.5892760.00.0-0.5646630.00.0-0.6290720.00.636931-1.5743860.00.00.0
1186-0.1172720.7088900.6770190.4119750.848367-0.1461020.5949810.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.5538122.470968e+00-7.095043e-010.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.127557-1.0505380.00.00.00.02.4988940.00.0-0.5646630.00.01.5990490.0-1.5819940.6421840.00.00.0
11870.779069-1.410656-0.6491581.7055150.848367-0.1461020.5949810.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0-0.2920023.154952e-01-7.095043e-010.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.1806980.7234530.00.00.00.0-0.5892760.00.0-0.5646630.00.0-0.6290720.00.636931-1.5743860.00.00.0
1188-0.6550760.708890-0.649158-0.881566-1.070890-1.3817100.5949810.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.5538123.154952e-01-7.095043e-010.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.02.5848871.4330490.00.00.00.00.9548090.00.0-0.5646630.00.01.5990490.00.636931-1.5743860.00.00.0
1189-0.1172720.7088900.6770190.4119750.8483671.0895050.5949810.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.5538122.470968e+00-7.095043e-010.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.4434990.0000000.00.00.00.00.9548090.00.0-0.5646630.00.01.5990490.0-1.581994-1.5743860.00.00.0